index

Markdown

Markdown is a way to make fancy documents. Make sure you “Knit” often – after every major change – to mitigate errors. Hashtags are how we make levels of a doc.

Next Level

Next level

Fourth level

etc.

Basic formatting

This is bold (that’s double asterisks). Or italics. Or code.

• this is the start of a list.
• next item.
• next item. make sure you have a space at the end of item.

1. this is a numbered list.
2. second item.

To add a hyperlink, do [link text](url). For example, go to the Sewanee website.

To link to sections of your document, do [link text](#section-name). For example, go to Markdown. ^keep in mind, no backticks, all lowercase, _ instead of spaces.

To add more vertical spaces between blocks ot text, use this:  , with lines between them.

 

 

Should be more space now.

To include an image – fun! First put an image inside the folder where you Rmd file is located. Then type ![](../images/full_image_filename_here){width="50%"}

RMarkdown

RMarkdown is just Markdown with R woven in.

You can do R stuff in the same line as text. For example 6 will show as 6. (That looks like backtick, lower-case-r, space, code, backtick).

You can also do a full-multi-line CHUNK of R stuff: Create with ```{r} on the first line and ``` on the last.

3+3

## [1] 6

Settings to control how R chunks appear:

• eval=TRUE: which actually runs the code; if eval=FALSE, it shows the code but doesn’t run it.

#this will be shown but not evaluated 
3+3

• echo=TRUE: which shows the code; if echo=FALSE, the code can run without being seen.

## [1] 8

• warnings=FALSE: which will turn off warning.

• fig.cap = "figure caption" adds a figure caption.

• fig.width = 7 example of figure width.

• fig.height = 4 example of figure height.

Bringing in real data

To manually set working directory while building up my RMarkdown file, just fo to Section > Set working directory > Source file locations.

library(readr)
energy <- read_csv("../data/IRENA data.csv", skip=1) #`skip=` to skip the first row at the top that is not actual data 

## Rows: 67200 Columns: 6
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (5): Country/area, Technology, Data Type, Grid connection, Electricity s...
## dbl (1): Year
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

energy %>% names

## [1] "Country/area"           "Technology"             "Data Type"             
## [4] "Grid connection"        "Year"                   "Electricity statistics"

energy %>% head

## # A tibble: 6 × 6
##   `Country/area` Technology      `Data Type`             `Grid connection`  Year
##   <chr>          <chr>           <chr>                   <chr>             <dbl>
## 1 Afghanistan    Total renewable Electricity Generation… On-grid            2000
## 2 Afghanistan    Total renewable Electricity Generation… On-grid            2001
## 3 Afghanistan    Total renewable Electricity Generation… On-grid            2002
## 4 Afghanistan    Total renewable Electricity Generation… On-grid            2003
## 5 Afghanistan    Total renewable Electricity Generation… On-grid            2004
## 6 Afghanistan    Total renewable Electricity Generation… On-grid            2005
## # ℹ 1 more variable: `Electricity statistics` <chr>

energy %>% tail

## # A tibble: 6 × 6
##   `Country/area` Technology `Data Type`                  `Grid connection`  Year
##   <chr>          <chr>      <chr>                        <chr>             <dbl>
## 1 Zimbabwe       Nuclear    Electricity Generation (GWh) On-grid            2019
## 2 Zimbabwe       Nuclear    Electricity Generation (GWh) On-grid            2020
## 3 Zimbabwe       Nuclear    Electricity Generation (GWh) On-grid            2021
## 4 Zimbabwe       Nuclear    Electricity Generation (GWh) On-grid            2022
## 5 Zimbabwe       Nuclear    Electricity Generation (GWh) On-grid            2023
## 6 Zimbabwe       Nuclear    Electricity Generation (GWh) On-grid            2024
## # ℹ 1 more variable: `Electricity statistics` <chr>

energy %>% pull(Technology) %>% unique %>% sort

##  [1] "Biogas"               "Coal and peat"        "Geothermal energy"   
##  [4] "Natural gas"          "Nuclear"              "Offshore wind energy"
##  [7] "Oil"                  "Onshore wind energy"  "Renewable hydropower"
## [10] "Solar photovoltaic"   "Total non-renewable"  "Total renewable"

Filtering code now

Here is a new section where I talk about what I’s doing.

#filter data
fenergy <- energy %>% 
  filter(`Country/area` == "Germany")

library(ggplot2)
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

p <- ggplot(fenergy,
       aes(x = Year,
           y = as.numeric(`Electricity statistics`),
           fill = Technology))+
  geom_area()
ggplotly(p)

## Warning in FUN(X[[i]], ...): NAs introduced by coercion

## Warning: Removed 29 rows containing non-finite outside the scale range
## (`stat_align()`).

Bringing in new datastes